Case Study
Ansys s'engage à préparer les étudiants d'aujourd'hui à la réussite, en leur fournissant gratuitement un logiciel de simulation.
Ansys s'engage à préparer les étudiants d'aujourd'hui à la réussite, en leur fournissant gratuitement un logiciel de simulation.
Ansys s'engage à préparer les étudiants d'aujourd'hui à la réussite, en leur fournissant gratuitement un logiciel de simulation.
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Case Study
“Ansys Lumerical simulation software met our criteria for accuracy, compatibility, user-friendliness, and support, and enabled us to design and optimize our photonic devices with confidence. The software made it easy to integrate fabrication process data for practical and realistic simulation results. Additionally, the software's customizability allowed us to tailor complex designs to our specific needs while leveraging advanced optimization methods. The quality technical support and resources ensured we got the most out of the software.”
— Mariam Aamer Benelfaquih, Senior R&D Photonics Design Engineer, LIGENTEC
The advancement in photonic integrated circuit (PIC) technology and applications is ushering in each new generation of photonics products with increasing performance criteria and complexity. Meeting demanding performance and complexity requirements while ensuring manufacturability and yield is a critical challenge faced in the PIC industry.
The design process can be challenging, time-consuming, and expensive, as it involves multiple iterations, fabrication, and testing. LIGENTEC is interested in optimizing complex PICs and photonic devices to meet specific performance criteria, including an optimized waveguide crossing with multiple figures of merit such as low insertion loss, minimum back-reflection, compact footprint, and low crosstalk.
LIGENTEC used Photonic Inverse Design (PID) capabilities in Ansys Lumerical FDTD for the design and optimization of its waveguide crossing. The company’s engineering solution involved specifying the initial geometry of the structure, defining the simulation parameters and material properties, setting the design objectives and constraints, and running the optimization algorithm to generate an optimized design.
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